Derinlik taramalı korelasyon ınterferomertrik mikroskopuyla nanoparçacıkların etiketsiz olarak algılanması

Detection of biological nanoparticles such as virus, protein aggregates or exosomes is critical for disease diagnosis and treatment monitoring applications, and for the development of novel biomarkers. Specifically, exosomes, cell derived vesicles, emerged as potential biomarkers for early detection of cancer and neurodegenerative diseases. Optical detection of these biological nanoparticles is quite challenging due to their small size and low refractive index contrast. Although fluorescence labeling based detection methods have emerged in recent years, these techniques rely on utilization of secondary probe molecules, which increases the complexity of the sample preparation. In addition to requiring complex labeling procedures, fluorescence-based detection also suffers from photo-blinking, bleaching and saturation. Label-free detection of nanoparticles overcomes these problems as well as provides the information about the intrinsic properties of the particles such as size and dielectric index. Widefield interferometric microscopy is a label-free method that allows visualization of nanosized particles, however it has several drawbacks such as limited sensitivity and sizing capability, and false interpretations of the results due to spatial variations of the surface capture probe density. In this thesis, we introduce two different interferometric detection systems to address the challenges present in interferometric microscopy. First, we introduce a low-cost interferometric biosensor developed by modifying a commercial flatbed scanner. We demonstrated the DNA hybridization and DNA-directed antibody immobilization in a microarray format, with a scan time of 10 seconds for an area of 4 mm x 4mm area (scalable to the size of an A4 paper). The developed system can be used for characterizing the capture probe density on sample substrate prior to biological nanoparticle detection experiments or can be used as a standalone biosensor, especially in low-resource settings. Secondly, we show that sensitivity (minimum detectable size) of interferometric microscopy can be improved by utilizing unique defocus response of nanoparticles. We developed the novel depth scanning correlation (DSC) interferometric microscopy technique, where depth scans are captured and correlation analysis on a pixel-by-pixel basis is performed using post-processing. We demonstrated detection of polystyrene nanoparticles smaller than 30 nm with a wide field of view of 300 µm x 200 µm. Furthermore, by applying Bayesian approach (prior knowledge) in the data analysis pipeline, characterization of the particles can be performed in a more robust way. A physical model for the interferometric nanoparticle images is applied to the acquired data through Markov Chain Monte Carlo (MCMC) analysis to estimate the particle parameters. Moreover, as potential applications, detection of exosomes isolated from the tumor cells and visualization of neutrophil extracellular traps (NETs) in a label-free format is demonstrated.